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Record W3212121730 · doi:10.14745/ccdr.v47i11a09

Invasive bacterial diseases in northern Canada, 1999 to 2018

2021· article· en· W3212121730 on OpenAlexafffundvenueabout
Grace Huang, Irene Martín, Raymond S. W. Tsang, Walter Demczuk, Gregory J. Tyrrell, Y Anita Li, Catherine Dickson, Francesca Reyes-Domingo, Susan G Squires

Bibliographic record

VenueCanada Communicable Disease Report · 2021
Typearticle
Languageen
FieldMedicine
TopicNeonatal and Maternal Infections
Canadian institutionsUniversity of AlbertaPublic Health Agency of Canada
FundersPublic Health AgencyPublic Health Agency of Canada
KeywordsIncidence (geometry)EpidemiologySerotypeIndigenousMedicineDiseaseDemographyPopulationHaemophilus influenzaeEnvironmental healthBiologyInternal medicineImmunologyMicrobiologyAntibioticsEcology

Abstract

fetched live from OpenAlex

BACKGROUND: (Hi), meningococcal disease (IMD) and group B streptococcus (GBS). Invasive bacterial diseases have a higher burden of disease in northern populations than the rest of Canada. METHODS: To describe the epidemiology of invasive bacterial diseases in northern Canada from 1999 to 2018, data for IPD, iGAS, Hi, IMD and GBS were extracted from the ICS program and the Canadian Notifiable Diseases Surveillance System (CNDSS) and analyzed. RESULTS: The annualized incidence rates for IPD, iGAS, Hi, GBS and IMD were 23.3, 10.5, 8.9, 1.9 and 1.1 per 100,000 population, respectively. The incidence of IPD, iGAS and Hi serotype b were 2.8, 3.2 and 8.8 times higher, respectively, in northern Canada than in the rest of Canada. Rates of disease decreased statistically significantly for IPD (β=-0.02) and increased statistically for iGAS (β=0.08) and Hi serotype a (β=0.04) during the study period. In Northern Canada, the annualized incidence rates for IPD, iGAS and Hi were statistically higher for Indigenous residents than for non-Indigenous residents. The highest incidence rates were among the very young and older age groups. CONCLUSION: Invasive bacterial diseases represent a high burden of disease in Canada's northern populations. Indigenous peoples, children and seniors are particularly at risk.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.978

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.234
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2021
Admission routes4
Has abstractyes

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